There are numerous software packages monitored as Portfolio Management Systems available. Mainly, these systems focus on the accounting functions necessary to track transactions within an account, keep the accounts in balance and allow for the reporting of gains and losses. Some systems include additional features such as contact management, financial planning calculations and rudimentary security analysis. Some allow for model portfolios to be created and then applied to an account with reports that will show the difference between the two. These systems may include the ability to have the system generate the transactions necessary to convert the actual holdings to the model portfolio, but all of those systems assume the conversion happens at the same point in time. They do not allow for the gradual transition from the actual portfolio to the model portfolio over time based on a set of pre-determined factors.
Some existing systems (especially those with financial planning functions) include portfolio return estimates, but they rely on long-term historical returns for each of the underlying investment classes. They do not allow estimates and resulting portfolio management decisions to be based on an advisor's short-term, forward-looking estimates of market performance. The result is that historical returns can be far greater than those expected in the short-term and can overstate the estimated return.
No systems are available to the inventor's knowledge that allow for the automating of the investment purchase and sale process according to predetermined criteria that can vary from client to client. No systems are available to the inventor's knowledge that would monitor every investment in every client's account and compare those predetermined levels against real-time pricing data and signal an alert when that criteria is breached.
There are a few systems available that aid an advisor in making buy and sell decisions for an individual security based on technical indicators, but these systems do not provide a comprehensive portfolio management system that extends those decisions to numerous clients while allowing different settings for each client. The result is that the advisor would make a decision on the security as a whole and then process a buy or sell across all accounts holding that security. This process does not take into account the specific circumstances in each account, including when it was purchased and whether or not there is a gain or loss.
To the inventor's knowledge, none of the existing systems available provide for the ability to assign an action level to each investment in an account and then alert the advisor when that action level was reached. For instance, suppose a client invested $100 k in security X but said that if security X lost $7,257 that the advisor should sell it. In these situations the advisor would need to manually enter a stop-loss order at the associated share price. Existing systems do not provide this capability, especially for numerous action levels on each investment in every client's account. The result is that advisors are not able to provide a sophisticated level of service and monitoring of a client's accounts. This can result in additional losses to the client.
Additionally, none of the existing PMS's monitor securities in real-time to determine the appropriate buy point based on technical analysis. This increases the possibility of an advisor buying a security at the wrong time.
There aren't any systems that allow an advisor to predict where a mutual fund will close on any given day and thus be able to make the buy/sell decision prior to that day's market close. This results in there being a 1-day lag between when the decision was made and when the transaction could be processed. In rapidly changing environments, this can result in additional losses or lost gains to the client.
Numerous systems exist in the prior art for determining when to sell a real investment. Most of these pertain to short term investing and/or day trading. The most basic incarnation of this system is a stop loss order. These are orders placed with a broker when an investment is bought. These systems have varying features, but most buyers place a fixed share price threshold that will trigger an investment to be sold. This threshold is always a single amount, not a plurality of amounts with variable liquidation percentages. Some systems are even automated through a computer program to track the price of an investment and make the selling trade when a dynamic share price threshold is broken by the downward movement in an investment's price. This system is commonly referred to as trailing stop loss.
These systems fail to adequately protect long-term investors. Both work in the context of actual dollars that prevents the stop loss from changing proportionally with the investment as it grows in value. Take this example. A standard stop loss order is placed with the purchase of an investment. The investment was purchased at $100 per share. The stop loss was placed at $95 per share. The investment then grows to $150 per share. The stop loss would still be at $95 per share leaving the investor a potential loss of $65 per share before the stop loss would be activated. That system allows for too much potential loss. A trailing stop loss would perform better. Instead of a stop loss of $95 per share in the previous example the investor utilizes a trailing stop loss of $5 per share. That means that when the investment is priced a $150 per share the stop loss trigger would be $145 per share. When originally placed the stop loss was 5% of the price per share. When the investment reaches $150 per share the stop loss of $5 per share will only be 3.33% of the price per share. The shrinking difference as a percentage would become undesirable to an investor who wants to allow the investment room to grow.
An improved system would be dynamic, that is, changing with an investments high price per share. It would have a plurality of triggers and a plurality of liquidation percentages. It would also be proportional, that being a percentage of an investments price per share. The system would utilize time sliced data on an investments price from a communication medium such as the Internet and automatically adjust the plurality of triggers in real-time. The system would automatically sell an investment when conditions are met or trigger an alert for manual intervention.
All known stop loss systems in the prior art sell 100% of an investment when a stop loss is triggered. This is well adapted to short term investors but is not optimal for long-term investors. Long-term investors are willing to accept a greater price fluctuation for an investment. There are also possibly negative tax implications for selling 100% of any investment. An improved system would allow for plurality of stop losses with a plurality of liquidation percentages. However no stop loss system such as this exists to help better control the selling of investments.